Job Description:

The Senior AI Engineer owns end-to-end delivery of AI features—from design to production—while raising the engineering bar through code quality, reliability, and mentoring. The engineer will convert architecture into robust implementations, proactively manage risks, and ensure observable, secure, and performant AI systems. Important to have Good Networking knowledge

Responsibilities:
Solution Engineering & Delivery

• Translate high-level designs into clear component contracts, APIs, and service boundaries.
• Implement LLM integrations, RAG pipelines, agents, tool/function calling, and prompt strategies.
• Own feature delivery for sprints/releases; maintain high code quality and documentation.

Modeling & Evaluation

• Fine-tune models when needed; design evaluation harnesses and metrics.
• Build A/B testing setups; track accuracy, latency, robustness, and task success rates.
• Conduct error analysis; iterate using feedback efficacy loops and prompt refinement.

Data & Retrieval Engineering

• Build ETL/ELT pipelines; curate datasets with metadata, lineage, and validation.
• Implement vector indexing (chunking, embeddings, reranking), tune chunk size & overlap.
• Enforce data governance: PII handling, redaction, consent, auditability.

MLOps & Platform Readiness

• Containerize workloads (Docker); orchestrate deployments (Kubernetes/Helm).
• Own CI/CD for ML: train → evaluate → package → deploy → monitor → rollback.
• Maintain model/agent registries, experiment tracking, and reproducible environments.

Software Engineering & Integration

• Build microservices and async inference paths; support batch/stream processing.
• Integrate with enterprise auth, observability, telemetry, and logging.
• Write unit/integration/e2e tests, performance benchmarks, and failure-injection tests.

Observability, Reliability & Performance

• Instrument with metrics/logs/traces; define SLOs (latency, throughput, error rate).
• Optimize inference: batching, caching (KV cache), quantization, token efficiency.
• Implement guardrails (safety filters, jailbreak detection), auto-evals and alerts.

Security & Compliance

• Apply secure coding practices; manage secrets, encryption, and least privilege.
• Ensure compliance (data residency, consent, audit trails); respect IP policies.
• Enforce policy-based access and content safety in user-facing features.

Collaboration & Mentoring

• Review designs/PRs; coach L3 engineers on best practices.
• Coordinate with AI Architects, Data Engineers, QA, and Product.

Education and Experience Required:

• Bachelor's or master’s degree in computer science, engineering, data science, machine learning, artificial intelligence, or closely related quantitative discipline.
• Typically, 7-10 years’ experience.

Knowledge and Skills:

• LLMs & Agents: Prompt engineering, function/tool calling, orchestration frameworks, RAG.
• ML/DS: Evaluation metrics (precision/recall, BLEU/ROUGE where relevant), error analysis.
• Data/RAG: Embeddings, similarity (cosine/IP), chunking, rerankers, vector DB operations.
• Backend: Python (FastAPI/Flask), microservices patterns.
• MLOps/Infra: Docker, Kubernetes, CI/CD, artifact management, GPU scheduling.
• Observability: Metrics/logging/tracing, dashboards, automated evaluation pipelines.
• Frameworks: PyTorch/TensorFlow, Hugging Face, LangChain/LlamaIndex.
• Data: Pandas, SQL/NoSQL, Parquet/Arrow, Kafka/queues.
• Vector DBs: FAISS, Milvus, pgvector, Pinecone, Weaviate.
• Ops: GitHub Actions/Azure DevOps, MLFlow/W&B

#LI-Hybrid

Health & Wellbeing

We strive to provide our team members and their loved ones with a comprehensive suite of benefits that supports their physical, financial and emotional wellbeing.

Personal & Professional Development

We also invest in your career because the better you are, the better we all are. We have specific programs catered to helping you reach any career goals you have — whether you want to become a knowledge expert in your field or apply your skills to another division.

Unconditional Inclusion

We are unconditionally inclusive in the way we work and celebrate individual uniqueness. We know varied backgrounds are valued and succeed here. We have the flexibility to manage our work and personal needs. We make bold moves, together, and are a force for good.

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Hewlett Packard Enterprise is EEO Protected Veteran/ Individual with Disabilities.

HPE will comply with all applicable laws related to employer use of arrest and conviction records, including laws requiring employers to consider for employment qualified applicants with criminal histories.

No Fees Notice & Recruitment Fraud Disclaimer

It has come to HPE’s attention that there has been an increase in recruitment fraud whereby scammer impersonate HPE or HPE-authorized recruiting agencies and offer fake employment opportunities to candidates.  These scammers often seek to obtain personal information or money from candidates.

Please note that Hewlett Packard Enterprise (HPE), its direct and indirect subsidiaries and affiliated companies, and its authorized recruitment agencies/vendors will never charge any candidate a registration fee, hiring fee, or any other fee in connection with its recruitment and hiring process.  The credentials of any hiring agency that claims to be working with HPE for recruitment of talent should be verified by candidates and candidates shall be solely responsible to conduct such verification. Any candidate/individual who relies on the erroneous representations made by fraudulent employment agencies does so at their own risk, and HPE disclaims liability for any damages or claims that may result from any such communication.